Chapter 4 - Metadata for Social Science Datasets¶
Metadata for Administrative and Social Science Data
Robert B Allen
[0000-0002-4059-2587]
<EMAIL_ADDRESS>Data are valuable but finding the right data is often difficult. This chapter reviews current approaches to metadata about numeric data and considers approaches that may facilitate the identification of relevant data. In addition, the chapter reviews how metadata support repositories, portals, and services. There are many emerging metadata standards, but they are applied unevenly so that there is no comprehensive approach. There has been greater emphasis on structural issues than on semantic descriptions.
INTRODUCTION¶
Evidence-based policy needs relevant data (Commission on Evidence-Based Policy, 2018; Lane, 2016). Such data is often difficult to find and use. The FAIR Open Access guidelines suggest that, ideally, data should be Findable, Accessible, Interoperable, and Reusable (FAIR).[^1] Broad and consistent metadata can support these needs. Metadata and other knowledge structures could also supplement and ultimately even replace text.
This chapter surveys the state of the art of metadata for numeric datasets, focusing on metadata for administrative and social science records. Administrative records describe details about the state of the world as collected by organizations or agencies. They include governmental, hospital, educational, and business records. By comparison, social science data generally is collected for the purpose of developing or applying theory.
We start by considering data and datasets (Section 2) and basic principles of metadata and their application to datasets (Section 3). Modern metadata is often implemented with Resource Description Framework (RDF) linked data (Section 4). Section 5 introduces ontologies and other semantic approaches. We then move to applications which use metadata. Section 6 examines repositories that hold and distribute collections of datasets. Section 7 describes services and techniques associated with repositories and Section 8 briefly describes the computing infrastructure for repositories.
DATA ELEMENTS AND DATASETS¶
While data may be incorporated in text, image, or video, here we focus on numeric observations recorded and maintained in machine-readable form. Individual observations are rarely used in isolation. Rather, they are typically collected into datasets.
A dataset is defined in the W3C-DCAT (W3C - Data Catalog Vocabulary)^2 as “a collection of data, published or curated by a single agent”^3 such as a statistical agency. There are many different types of datasets; they differ in their structure, their source, and their use. A given data element may appear in many different datasets and may be numerically combined with other data to form derived data elements which then appear in still other datasets. In some cases, they are single vectors of data; in other cases, they comprise all the data associated with one study or across a group of related datasets. Reference datasets are generally collected and archived because they are of enduring value and can be used for answering many different types of questions. Other datasets, such as an individual’s medical records, are associated with a relatively narrow set of applications.
There is wide variability in the organization and contents of datasets, as well as in the extent to which datasets are validated and curated. Potentially with frameworks such as the SDMX (Statistical Data and Metadata eXchange) Guidelines for the Design of Data Structure Definitions,^4 concise structured descriptions can be developed for how data elements are combined to form datasets.
METADATA SCHEMAS AND CATALOGS¶
Many datasets are available; the DataCite repository alone contains over five million datasets. Metadata can support users in finding datasets and enable users to know what is in them. Metadata are short descriptors which refer to a digital object. However, there is tremendous variability in the types of metadata and how they are applied. One categorization of metadata identifies structural (or technical), administrative, and descriptive metadata (Riley, 2017). Structural metadata includes the organization of the files. Administrative metadata describes the permissions, rights, preservation and usage relating to the data.[^5] Descriptive metadata covers the contents.
A metadata element describes an attribute of a digital object. The simplest metadata (e.g., a Digital Object Identifier (DOI) or ORCiD^6) identifies the digital object or its creator.[^7] Metadata elements are generally part of a schema, or frame. DCAT[^8] is a schema standard for datasets that is used by many repositories such as data.gov. Other structured frameworks for datasets include the DataCite^9 metadata schema and the Inter-university Consortium for Political and Social Research Data Documentation Initiative (ICPSR DDI, see Section 6.1). ISO 19115-1:2014 establishes a schema for describing geographic information and services. ^10
The schema specifications provide a flexible framework. For instance, DCAT allows the inclusion of metadata elements drawn from domain schema and ontologies. Some of these domain schemas are widely used resources which DCAT refers to as assets. Figure 1 shows a fragment of properties (i.e., metadata elements) from an implementation of the Schema.org[^11] dataset schema to describe gross domestic product.
Figure 4.1: Fragment of GDP properties described by the Schema.org dataset schema.^12
Metadata terms for an application are often assembled into namespaces from different metadata schemas. Metadata Application Profiles[^13] provide constraints on the types of entities that can be included in the metadata for a given application. Moreover, application profiles can be used to validate standards. For instance, the DCAT Application Profile for data portals in Europe (DCAT-AP) supports the integration of data drawn from repositories in different jurisdictions in the EU.^14
A collection of dataset schema,[^15] such as all the datasets in a repository, forms a catalog. For data streams, there needs to be continuity but also the ability to update the records. In some cases, there may be relatively infrequent periodic updates. These could be given version numbers rather than an entirely new DOI.[^16] However, collections of highly dynamic data streams present challenges; most of the data stay the same but some of the data and/or metadata (e.g., number of records) change.
LINKED DATA¶
RDF (Resource Description Framework) extends XML by requiring triples which assert a relationship (property) between two identifiers: “identifier – property - identifier”. RDF Schema (RDFS) extends RDF by supporting subclass relationships. A graph is formed by linking triples.
Hierarchical classification systems are another knowledge structure with a long history. Indeed, Schema.org is based around a hierarchical ontology. Simple classification relationships are handled by the Simple Knowledge Organization System (SKOS). SKOS represents the hierarchical structure of traditional thesauri with RDFS. Collections of data organized by SKOS are often described as “linked data”.
Depending on the rigor with which they are developed, these collections can support limited logical inference. Many administrative and social-science-related thesauri, such as EDGAR and those of the World Bank and the OECD, have now been implemented with SKOS. A knowledgebase is, primarily, a SKOS graph that links real-world entities. For example, Wikidata^17 is an effort to develop a knowledgebase based on structured data from Wikimedia projects, and VIVO^18 is a knowledge graph of scholarship.
But there are also many stand-alone classification schemes. The Extended Knowledge Organization System (XKOS)^19 was developed to allow classification systems to be incorporated into a SKOS framework.
RICHER SEMANTICS¶
Ontologies provide a coherent set of relationships between entities which cover a given domain. Well-constructed ontologies can support logical inference. Some vocabularies such as Dublin Core, which is implemented in RDF, are said to have an ontology, but they are limited because relationships among the terms are not specified. FOAF (Friend of a Friend) provides a somewhat richer ontology which includes attributes associated with people. Still more extensive ontologies often use OWL (Web Ontology Language) which can support stronger logical inference than RDFS.
One way to coordinate across terms is an upper ontology. Upper ontologies provide top-down structures for the types of entities allowed in domain and application ontologies. One of the best-known upper ontologies is the Basic Formal Ontology (BFO) (Arp, Smith, & Spear, 2015), which is a realist, Aristotelian approach. At the top-level, BFO distinguishes between Continuants (endurants) and Occurrents (perdurants) and also between Universals and Particulars (instances). Many biomedical ontologies based on BFO are collected in the Open Biomedical Ontology (OBO) Foundry.^20
There are fewer rich ontologies dealing with social science content than for natural science. Social ontology, that is, developing rigorous definitions for social terms, is often a challenge. It is difficult to define precisely what is a family, a crime, or money. In most cases, an operational or approximate definition may suffice when formal definitions are difficult. However, those operational definitions often do not interoperate well across studies.
DATA REPOSITORIES AND COLLECTIONS OF DATASETS¶
A data repository holds datasets and related digital objects. Ideally, it contains a stable collection selected according to a collection policy. It is organized by metadata and knowledge structures. It provides access to the datasets and typically supports search.
The Inter-University Consortium for Political and Social Research (ICPSR)¶
ICPSR^21 is a major repository of public-use social science and administrative datasets derived mostly from questionnaires and surveys. We go into depth about it here because the ICPSR Data Documentation Initiative (DDI)^22 (e.g., Vardigan, Heus, & Thomas, 2009) is especially well-crafted.[^23] The DDI codebook saves the exact wording of all the questions and ICPSR provides an index of all variable names. DDI-Lifecycle is an extension that describes the broader context in which the survey was administered as well as the details about the preservation of the file (see Section 7.1). DDI uses XKOS to provide linked data. Figure 2 shows the ICPSR DDI metadata schema.
Figure 4.2: ICPSR DDI metadata elements.
Version
Study Title
Alternate Title
PIs & Affiliation
Funding Agencies
Summary
Subject Terms
Geographic Coverage Areas
Geographic Representation
Study Time Periods and Time Frames
Collection Notes
Study Purpose
Study Design
Description of Variables
Sampling: Sampling Procedure, Sampling Unit, Sampling Notes
Oversampled Group
Time Method
Data Source Type
Mode of Collection
Weight
Response Rates
Scales
Analysis Unit
Unit of Observation
Smallest Geographic Unit
Data Format
Restrictions
Version History
The ICPSR metadata elements incorporate aspects of the implementation and design of research studies. However, many of the ICPSR metadata elements are not independent; potentially, they could be interlinked with terms such as organizations, locations, individuals, and research designs from other knowledgebases. Moreover, they could be linked with higher-level workflows and mechanisms (see Sections 7.1, 7.5).
Additional Examples of Repositories¶
Statistical data collection is a core function of government. Such collections often emphasize social data such as employment, criminal justice, and public health. They also include related indicators such as agricultural and industrial output and housing. Most countries have national statistical agencies such as Statistics New Zealand, and the Korean Social Science Data Archive (KOSSDA). European datasets are maintained in the Consortium of European Social Science Data Archives (CESSDA)^24 and the European Social Survey.^25 Australia has a broad data management initiative, ANDS.[^26] Many U.S. federal governmental datasets are collected at data.gov. In addition, there are many other social survey repositories[^27] and many U.S. states and cities have online statistics sites at varying levels of sophistication.
There are also many non-governmental and inter-governmental agencies such as the OECD, the World Bank, and the United Nations that manage datasets. Similarly, there are very large datasets from medical research such as from clinical trials and from clinical practice including Electronic Health Records (EHRs).
Many datasets are produced, curated, and used in the natural sciences such as astronomy and geosciences. Some of these datasets have highly automated data collection, elaborate archives, and established curation methods. Many repositories contain multiple datasets for which access is supported with portals or data cubes (see Section 7.4). For instance, massive amounts of geophysical data and related text documents are collected in the EarthCube^28 portal. The science.gov portal is established by the U.S. Office of Science Technology and Policy. NASA supports approximately 25 different data portals. Each satellite in the Earth Observation System (EOS) may provide hundreds of streams of data,^29 with much common metadata. Likewise, there are massive genomics and proteomics datasets which are accessible via portals such as UniProt^30 and the Protein Data Bank^31 along with suites of tools for exploring them.
Repository Registries¶
There are a lot of different repositories, so it is useful to have a registry with a standard schema structure for describing them. The Registry of Research Data Repositories^32, which is operated by DataCite, links to more than 2000 repositories each of which holds many datasets. Each of those repositories is described by the re3data.org schema (Rücknagel, Vierkant, et al., 2015).
Ecosystems of Texts and Datasets¶
Datasets are often associated with text reports, whether they describe the development of the datasets or their use. Ultimately, we would like to be able to move seamlessly from datasets to texts and other related materials. However, as demonstrated by several of the papers in this volume, it is often difficult to extract details about datasets from legacy publications.
Text associated with a dataset may be used to support searching for it. Indeed, Google Dataset Search uses texts marked up with Schema.org JSON-LD (JavaScript Object Notation for Linked Data) micro-data to generate an index.
Going forward, great value can be achieved by persuading editors and authors to clearly cite and deposit datasets. In some cases, a separate data editor may be appointed. The Dryad Digital Repository^33 captures datasets from scholarly publications. It requires the deposit of data associated with scholarly papers accepted for publication. Such datasets are most often used to validate the conclusions of a research publication, but they may also be used more broadly.
Research datasets may be given DOIs^34 and cited in much the same way that research reports are cited. Formal citations can support tracing the origins of data used in analyses and help to acknowledge the work of the creators of the datasets.
Information Institutions and Organizations¶
The Open Archival Information System (OAIS) provides a reference model for the management of archives (Lee, 2010). A key part of the model is the inclusion of preservation planning and the requirement for stable administration over time. These attributes are part of all information institutions. Libraries, archives, and museums have formal collection management strategies, metrics, and policies.
In addition to traditional information institutions, there are now many other players. CrossRef^35 and DataCite are DOI registration agencies. CrossRef is a portal to metadata for scholarly articles, while DataCite provides metadata for digital objects associated with research. Schema.org’s primary mission is to provide a structure that improves indexing by search engine companies. Still other organizations such as HL7[^36] and KEGG[^37] manage controlled vocabularies and frameworks. These organizations are increasingly adopting best practices similar to those of traditional information organizations.
REPOSITORY SERVICES¶
Analysis Platforms and Decision Support Systems¶
There is an increasingly rich set of analytic tools. Some of the earliest tools were statistical packages such as SPSS, R, SAS, and STATA. These were gradually enhanced with data visualization and other analytic software. The current generation of tools such as Jupyter^46, RSpace, and eLab notebooks (ELN) integrate annotations, workflows, raw data, data analysis, and annotations into one environment.
Virtual research environments (VREs) are typically organized by research communities to coordinate datasets with search and analytic tools. For instance, the Virtual Astronomy Observatory (VAO) uses Jupyter to provide users with a robust research environment. WissKI^47 is a platform for coordinating digital humanities datasets which are based on Drupal. Decision Support Systems (DSS) are generally focused on finding optimal solutions in a parameter space. They often draw on data warehouses though recently they have begun to incorporate feeds from unstructured data (e.g., web searches).
Most repositories support search on metadata terms. In addition, some repositories have developed their own powerful data exploration tools such as ICPSR Colectica^48 for DDI and the GSS Data Explorer^49. The Amundsen data discovery and metadata engine^50 uses metadata elements to provide a table explorer. Potentially, interactive visualization tools such as TableLens (Rao & Card, 1994) could also be employed.
Metadata Development, Standardization, and Management¶
Metadata, whether for texts or datasets, needs to be complete, consistent, standardized, machine processable, and timely (Park, 2009). Metadata registries provide clear definitions and promote standardization (ISO/IEC 11179). For instance, the Marine Metadata Interoperability Ontology Registry and Repository^51 records usage of different metadata terms. A registry may interoperate with editing tools for developers (Goncalves, O’Connor, et al., 2019). These tools may suggest candidate metadata terms. One of the keys to the development of good metadata is the involvement of a community that cares about the results.
Data Cubes, Data Warehouses, and Data Exchanges¶
An organization such as a large business often has many different databases. The data in the databases will likely have different formats and definitions and can be organized in a multidimensional cube. Some of cube’s cells may be well-populated with data that appears across many of the databases, but there will also be sparsely populated regions and cells. Online Analytical Processing (OLAP) users can generate different views of the data by drilling-down, rolling-up, and slicing-and-dicing across cells. To facilitate retrieval, there can be a rich pre-coordinated index for common queries. Other queries can be implemented with slower methods such as hashing or B-trees.
While many organizations now have integrated enterprise data management systems, data cubes are still useful for warehousing data and for exchanging it across organizations. For instance, the W3C Data Cube^52 standard is applied in inter-organizational projects such as EarthCube^53. SDMX^54 enables data exchange among statistical agencies in the EU.
Production Workflows, Research Workflows, and Research Objects¶
Entities change over time, yet many knowledge representation frameworks do not model change. To represent change, models need to represent transitions, processes, and other sequential activities. Such modeling is closer to state machines, Petri Nets, process ontologies, the Unified Modeling Language (UML) or even programming languages than to traditional knowledge representation.
One way to document a research project is by saving files developed during the study (Borycz & Carroll, 2018). Data files (e.g., Excel files) are just one type of artifact from a research program; other research objects include workflows. Workflows are a natural fit for describing research methods and analyses (Austin, et al., 2017). The Taverna^55 workflow tool has been used for the MyExperiment^56 project. It provides a framework for capturing and posting Taverna and other types of research workflows and incorporates simple ontologies such as FOAF. Workflows can also be used to specify and document statistical analyses; several of the analysis platforms described in Section 7.2 support them. Sequential activities in the management of repositories are often tracked with workflows. For instance, the Generic Statistical Information Model (GSIM)^57 specifies workflows for the production of datasets by statistical agencies.
Semantic Modeling and Direct Representation¶
Semantic models attempt to represent entities. They could support unified descriptions of functionality, transitions of complex continuants, and sequential activities (Allen, 2018). Changes in semantic models are a form of qualitative simulation. While traditional knowledge representation is usually implemented with ontologies, models which allow transitions are more like programming languages. Although semantic modeling might be implemented by process ontologies, we have focused on the use of an object-oriented programming language which supports threads to allow parallel concurrent event streams and potentially to develop a “unified temporal map”. Such semantic simulations may be useful for modeling historical events. For instance, a community described in a newspaper may be cast into a “community model”. These go beyond social ontology to model social mechanisms (Ylikoski, in press).
In addition, Allen (2015, 2018) has proposed rich semantic modeling of entire research reports and datasets. Structured evidence and argumentation about claims might then be applied for the evaluation of the models. Ultimately, such “direct representation” may replace text as the primary representation for research and scholarship.
INFRASTRUCTURE¶
Repository Servers¶
Semantic representations may be implemented with triplestores. Triplestores facilitate logical inference, but retrieval may be more efficient with relational databases. Many metadata catalogs are implemented with relational databases. Thus, they use SQL and are often characterized by UML Class Diagrams. Information models (e.g., National Information Exchange Model (NIEM)^58) which could be used for metadata registries may be implemented as data dictionaries.
Some repositories are federated with the Open Archives Initiative Protocol for Metadata Harvesting (OAI-PMH)^59. This allows the “harvesting” of metadata from separate repositories. OAI-PMH is increasingly used as an API to allow external users to query and interact with the federated set of metadata.
Cloud Computing¶
We are well into the era of cloud computing (Foster & Gannon, 2017), allowing flexible allocation of computing, networking and storage resources, which facilitates Software as a Service (SaaS). The compatibility of the versions of software packages needed for data management is often a challenge. Containers, such as those from Docker, allow compatible versions of software to be assembled and run on a virtual computer. A cloud-based virtual machine can hold datasets, workflows, and the programs used to analyze the data, which can be a complete digital preservation package.
Highly networked data centers facilitate the Internet of Things (IoT) which generates massive and dynamic data. Increasingly, cloud computing is supporting edge computing and append-only stores which can capture streaming data. These technologies will provide the foundation of smart cities and have implications for the kinds of questions we may ask about social behavior.
CONCLUSION¶
Many datasets, especially legacy datasets, are difficult to find and access. Some of the biggest issues for the retrieval of datasets concern information organization, which helps to provide context. Metadata supports the discovery and access to datasets.
More attention to metadata would also further support evidence-based policy. We need richer, more systematic, and more interoperable metadata standards. We need to improve the metadata associated with existing datasets. And we need to aggressively upgrade the application of high-quality metadata and knowledge organization systems to datasets as they are created.
ACKNOWLEDGMENTS¶
Julia Lane and members of NYU’s Center for Urban Science and Progress provided useful advice and comments.
REFERENCES {#references .ListParagraph}¶
Allen, R.B. (2015) Repositories with direct representation, Networked knowledge representation systems, arXiv: 1512.09070
Allen, R.B. (2018) Issues for using semantic modeling to represent mechanisms, arXiv:1812.11431
Allen, R.B., & Kim, YH. (2017/2018) Semantic modeling with foundries, arXiv:1801.00725
Arp, R., Smith, B., & Spear, A.D. (2015) Building ontologies with basic formal ontology, MIT Press, Cambridge. MA.
Austin, C.C., Bloom, T., Dallmeier-Tiessen, S., Khodiyar, V.K., Murphy, F., Nurnberger, A., et al. (2017). Key components of data publishing: Using current best practices to develop a reference model for data publishing. International Journal on Digital Libraries, 18(2) 77–92, doi:10.1007/s00799-016-0178-2
Borycz, J., & Carroll, B. (2018) Managing digital research objects in an expanding science ecosystem: 2017 conference summary. Data Science Journal, 17, doi: http://doi.org/10.5334/dsj-2018-016
Commission on Evidence-Based Policymaking (2018) The Promise of Evidence-Based Policymaking, https://www.cep.gov/cep-final-report.html
Foster, I., & Gannon, D.B. (2017) Cloud computing for science and engineering, MIT Press, Cambridge, MA.
Gonçalves, R.S., O’Connor, M.J., Martínez-Romero, M., Egyedi, A.L., Willrett, D., Graybeal, J., & Musen, M.A. (2019) The CEDAR workbench: an ontology-assisted environment for authoring metadata that describe scientific experiments. arXiv: 1905.06480
InterPARES2 Project (2008) A framework of principles for the development of policies, strategies and standards for the long-term preservation of digital records, http://www.interpares.org/public_documents/ip2(pub)policy_framework_document.pdf
Lane, J. (2016) Big data for public policy: The quadruple helix, Journal of Policy Analysis and Management, 35(3), doi: 10.1002/pam.21921
Lee, C.A. (2010) Open Archival Information System (OAIS) reference model. Encyclopedia of library and information sciences (3^rd^ Edition). CRC Press, doi: 10.1081/E-ELIS3-120044377
Park, J-R., (2009) Metadata quality in digital repositories: A survey of the current state of the art. Cataloging & Classification Quarterly, 47, 213–228, 2009, doi: 10.1080/01639370902737240
Rao, R., & Card, S.K. (1994) The Table Lens: Merging graphical and symbolic representations in an interactive focus+context visualization for tabular information, ACM SIGCHI, 318-322, doi: 10.1145/191666.191776
Riley, J. (2004) Understanding metadata: What is metadata, and What is it for?: A primer, NISO Press, Bethesda, MD. ISBN: 978-1-937522-72-8
Rücknagel, J., Vierkant, P., Ulrich, R., Kloska, G., Schnepf, E., Fichtmüller, D. et al. (2015) Metadata schema for the description of research data repositories: version 3.0 (29), doi: 10.2312/re3.008
Vardigan, M., Heus,P., & Thomas, W. (2008) Data documentation initiative: Toward a standard for the social sciences. International Journal of Digital Curation. 3**(1). doi:** 10.2218/ijdc.v3i1.45
Whyte, A., & Wilson, A. (2010) How to appraise and select research data for curation. DCC How-to Guides. Edinburgh: Digital Curation Centre. http://www.dcc.ac.uk/resources/how-guides
Wilkinson, M.D., Dumontier, M., Aalbersberg, I.J.J., Appleton, G., Axton, M., Baak. A., et al. (2016) The FAIR guiding principles for scientific data management and stewardship, Scientific Data, 3, 160018. doi: 10.1038/sdata.2016.18
Ylikoski, P. (to appear) Social mechanisms. The Routledge handbook of mechanisms and mechanical philosophy, Routledge, edited by S. Glennan and P. Illari
[^1]: The FAIR Guidelines have been extended from scholarly texts to datasets (Wilkinson, Dumontier, et al., 2018).
[^5]: “Administrative” in the context of metadata thus is distinct from “administrative data”.
[^7]: Such operators must be unambiguous. For example, DOIs (http://doi.org) were developed for scholarly journals and are assigned by publishers, with a part of the DOI code being a unique publisher ID. While a DOI may identify more than one dataset, version numbers distinguish the datasets. For instance, the entire GSS (General Social Survey) has only one DOI, but it is possible to drill down through the different datasets by specifying version numbers.
[^8]: https://www.w3.org/TR/vocab-dcat/. See note 2.
[^11]: Schema.org is a project of a consortium of search-engine companies. The Schema.org dataset schema (https://schema.org/Dataset) is used by Google Dataset Search.
[^13]: See, e.g., Guidelines for Dublin Core Application Profiles: https://www.dublincore.org/specifications/dublin-core/profile-guidelines/ We propose that Ontology Application Profiles, analogous to Metadata Application Profiles, could be used for specifying terms for a given application selected from different foundry ontologies.
[^15]: This differs from library or archival collections, which are usually thematically related, and for which the selection of items for inclusion is defined by an express collection policy.
[^16]: The challenges of metadata for data streams are related to the cataloguing of different editions of a work and of serials in a text-based library.
[^23]: DDI is also used for datasets from other organizations such as the National Opinion Research Center (NORC).
[^26]: Australia National Data Service: https://www.ands.org.au/
[^27]: There are additional collections at http://data.census.gov, http://gss.norc.org. [ ]{.underline} http://electionstudies.org, http://psidonline.isr.umich.edu, and http://www.nlsinfo.org.
[^36]: Health Level Seven International, https://www.hl7.org/
[^37]: Kyoto Encyclopedia of Genes and Genomes, https://www.genome.jp/kegg/
[^38]: See also, e.g., http://www.dcc.ac.uk/digital-curation/planning-preservation
[^39]: Controlled Lots of Copies Keep Stuff Safe, https://clockss.org/
[^41]: The policies are based on the International Research on Permanent Authentic Records in Electronic Systems (InterPARES) standard. https://interparestrust.org/
see also, http://www.dcc.ac.uk/resources/repository-audit-and-assessment/drambora.
[^45]: The term micro-data is used in two distinct ways. In the context of HTML, it is associated with embedding Schema.org codes into web pages similar to micro-formats. In the context of survey data, it refers to individual-level data.
GSIM is coordinated with the Common Statistical Production Architecture (CSPA). https://unstats.un.org/unsd/nationalaccount/workshops/2015/gabon/BD/CSPA-ENG.pdf


Command List Changed
ls
- list directory
cd
- change directory
touch
- create empty file or update modification time
git add
- adds all of the files in the directory
git commit
- records changes to the repository
git pull
- Fetch from and and integrate with another repository or a local branch
clear
- clears the screen
resert
- resets the terminal display
pbpaste
- paste clipboard contents
pbcopy
- copies file contents to clipboard
ls
- short listing
git push
- update remote refs along with associated objects
git status
- show the working tree status


Jubilation in Yenagoa as APC supporters storm major roads
by Oladeinde OlawoyinSupporters of the All Progressives Congress (APC) in Bayelsa State on Monday stormed major streets of Yenagoa, the state capital, to celebrate the victory of their party in Saturday’s election.
The supporters, in their tens and hundreds, took over major streets in the capital city, chanting victory songs.
A PREMIUM TIMES reporter in the capital city reports that the supporters took over the popular Tombia Roundabout.
Some of the supporters who spoke in an interview with our reporter expressed their delight at the result of the election.
“Lyon is a man of the people and that’s why he won convincingly,” a supporter of the party told PREMiUM TIMES at Edepie.
The party’s governorship candidate in Bayelsa State, David Lyon, was declared winner of the Bayelsa State 2019 governorship election.
The declaration was made Monday morning by Faraday Orumwese, Vice Chancellor of the University of Benin and the returning officer in the election.
The returning officer announced that Mr Lyon polled 352,552 votes to defeat Duoye Diri of the Peoples Democratic Party (PDP) who polled 143, 172 votes.
The total number of registered voters was announced as 922, 562 and the number of accredited voters was put at 517,883.
PREMIUM TIMES reported how Mr Lyon won in six of the eight local governments in the state.
On Monday, there was traffic snarl along Amasoma Road as supporters of the party trooped out to celebrate its victory. The same was the situation at Tombia Roundabout and along Edepie Road.


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Put your consent form here. If you are a worker and are viewing this please decline the HIT. This requester doesn't know what they are doing.


GradesSDK is a tool for integration of Grades classification system into your app. It provides a set of functions and for simple communication with the Grades service, eliminating the need of using HTTP requests during your development.
Links:
npm install grades-sdk
In order to gain access to Grades API, it is first necessary to perform the following two-step process:
const sdk = require('grades-sdk');
const {GradesURL} = require("grades-sdk/lib/apiRequestor");
const grades = new sdk.GradesSDK(GradesURL.Live, clientId, clientSecret);
const myCourse = grades.getCourse('NI-XYZ');
All set! The grades
instance can be used to retrieve the semester code or to return a Course
instance. To manage a course – its definition hierarchy, student groups and student classifications, the Course
instance (named myCourse
in the code snippet above) can be used.
The following code snippets show how the module can be used to perform a number of basic tasks.
async function getSemesterCode() {
const semesterCode = await grades.getSemesterCode()
console.log(semesterCode);
}
async function getInfoForMyCourse() {
const courseInfo = await myCourse.getCourseInfo();
console.log(courseInfo);
}
async function getDHForMyCourse() {
const definitionHierarchy = await myCourse.definitions.getDefinitionHierarchy();
console.log(definitionHierarchy);
}
It will be necessary to add the following require statement to the top of your file to gain access to the Definition
class provided by the module.
const {Definition} = require("grades-sdk/lib/definition");
The Definition
constructor accepts any object that implements the DefnitionInterface
. More detailed information about the classes and interfaces provided by this module can be found in the documentation. -> Just pull this project and open the docs/index.html
file in a browser.
async function addDefinitionIntoDH() {
const newDefinition = new Definition({
identifier: 'test_definition',
parentIdentifier: '',
namesForLocales: {en: 'Test definition', cs: 'Testovací definice'},
courseCode: 'PI-ARB',
semesterCode: 'B202',
expression: null,
classificationType: "QUIZ",
evaluationType: "MANUAL",
minimumValue: 0,
minimumRequiredValue: 7,
maximumValue: 10,
valueType: "NUMBER",
hidden: false
});
await myCourse.definitions.createDefinitions(newDefinition);
}
async function deleteDefinition(definitionIdentifier) {
await myCourse.definitions.deleteDefinitions(definitionIdentifier);
console.log("Definition deleted");
}
async function getGroupClassifications(groupCode) {
const studentsClassifications = await myCourse.classifications
.getStudentClassificationsForGroup(groupCode);
}
Generated using TypeDoc


--- layout: default ---
With more and more people getting connected to the internet via their phones nowadays, Firefox for Android a key product for Mozilla to remain relevant and influence the market. Participate in the suport sprint and help our users to get better Firefox experience in your language.
learn more
learn more
Still interested?
Get involved!


---
title: "Resources Track PC"
updated: 2016-08-30 00:00:00
layout: default
group: organization
menu: sub
ordered: 2
status: published
---
| Maribel Acosta |
Karlsruhe Institute of Technology, Germany |
| Ahmet Aker |
Sheffield University, UK |
| Diana Bental |
Heriot-Watt University, UK |
| Abraham Bernstein |
University of Zurich, Switzerland |
| Eva Blomqvist |
Linköping University, Sweden |
| Sarven Capadisli |
University of Bonn, Germany |
| Tim Clark |
Massachusetts General Hospital / Harvard Medical School, USA |
| Oscar Corcho |
Universidad Politécnica de Madrid, Spain |
| Philippe Cudre-Mauroux |
University of Fribourg, Switzerland |
| Claudia d’Amato |
University of Bari, Italy |
| Mathieu D'Aquin |
The Open University, UK |
| Victor de Boer |
VU Amsterdam, Netherlands |
| Daniele Dell’Aglio |
BEIB, Politecnico di Milano, Italy |
| Gianluca Demartini |
University of Sheffield, UK |
| Stefan Dietze |
L3S Research Center, Germany |
| Ying Ding |
Indiana University, USA |
| Michel Dumontier |
Stanford University, USA |
| Fajar J. Ekaputra |
Technische Universität Wien, Austria |
| Miriam Fernandez |
Knowledge Media Institute, UK |
| Aldo Gangemi |
Université Paris 13 and CNR-ISTC, France |
| Jose Manuel Gomez-Perez |
Expert System, Spain |
| Alejandra Gonzalez-Beltran |
University of Oxford, UK |
| Pascal Hitzler |
Wright State University, USA |
| Robert Hoehndorf |
King Abdullah University of Science and Technology, Saudi Arabia |
| Rinke Hoekstra |
University of Amsterdam, Netherlands |
| Matthew Horridge |
Stanford University, USA |
| Andreas Hotho |
University of Wuerzburg, Germany |
| Antoine Isaac |
Europeana and Vrije Universiteit Amsterdam, Netherlands |
| Simon Jupp |
European Bioinformatics Institute, UK |
| Elmar Kiesling |
TU Wien, Austria |
| Olga Kovalenko |
TU Wien, Austria |
| Tobias Kuhn |
VU University Amsterdam, Netherlands |
| Markus Luczak-Roesch |
University of Southampton, UK |
| Maria Maleshkova |
Karlsruhe Institute of Technology, Germany |
| Fiona McNeill |
Heriot-Watt University, UK |
| Chris Mungall |
Lawrence Berkeley National Laboratory, USA |
| Vinh Nguyen |
Wright State University, USA |
| Bijan Parsia |
University of Manchester, UK |
| Heiko Paulheim |
University of Mannheim, Germany |
| Silvio Peroni |
University of Bologna, Italy |
| Valentina Presutti |
STLab (ISTC-CNR), Italy |
| Giuseppe Rizzo |
ISMB, Italy |
| Mariano Rodríguez Muro |
IBM Research, USA |
| Satya Sahoo |
Case Western Reserve University, USA |
| Cristina Sarasua |
University Koblenz - Landau, Germany |
| Stefan Schlobach |
Vrije Universiteit Amsterdam, Netherlands |
| Jodi Schneider |
University of Pittsburgh, USA |
| Stian Soiland-Reyes |
University of Manchester, UK |
| Valentina Tamma |
University of Liverpool, UK |
| Krishnaprasad Thirunarayan |
Wright State University, USA |
| Ramine Tinati |
University of Southampton, UK |
| Raphaël Troncy |
EURECOM, France |
| Natalia Villanueva-Rosales |
University of Texas at El Paso, USA |
| Simon Walk |
Graz University of Technology, Austria |
| Peter Wetz |
TU Wien, Austria |
| Marcia Zeng |
Kent State University, USA |
| Jun Zhao |
University of Oxford, UK |
| |
| Reihaneh Amini |
Wright State University, USA |
| Sebastian Bader |
Karlsruhe Institute of Technology, Germany |
| David Carral |
Wright State University, USA |
| Lu Chen |
Wright State University, USA |
| Maxime Déraspe |
Laval University, Canada |
| Djellel Difallah |
University of Fribourg, Switzerland |
| Jhonatan Garcia |
University of Aberdeen, Scotland |
| Nuria García-Santa |
Expert System, Spain |
| Kalpa Gunaratna |
Wright State University, USA |
| Karl Hammar |
Jönköping University, Sweden |
| Robin Keskisärkkä |
Linköping University, Sweden |
| Adila Krisnadhi |
Wright State University, USA |
| Sarasi Lalithsena |
Wright State University, USA |
| María Poveda-Villalón |
Universidad Politénica de Madrid, Spain |
| Sambhawa Priya |
Lehigh University, USA |
| José Redondo-García |
EURECOM, France |
| Laura Rettig |
University of Fribourg, France |
| Daniel Schlör |
University of Würzburg, Germany |
| Saeedeh Shekarpour |
Wright State University, USA |
| Ruben Verborgh |
University Ghent, iMinds, Belgium |
| Ran Yu |
University of Hannover, Germany |
| Amrapali Zaveri |
Stanford University, USA |
| |


--- layout: layouts/base.html title: Running events --- {{title}} {% for event in races %} {{ event.title }} {{ event.description }} {% endfor %}


To customize the size and position of elements in a layout, use the
flex
, offset
, and flex-order
attributes.
Add the flex
attribute to a layout's child element, and it
will flex (stretch) to fill the available area.
A layout child's flex
attribute can be given an integer value from 0-100.
The element will stretch to the percentage of available space matching the value.
The flex
attribute value is restricted to 33, 66, and multiples
of five.
For example: flex="5", flex="20", "flex="33", flex="50", flex="66", flex="75", ...
.
See the layout options page for more information on responsive flex attributes.
Add the flex-order
attribute to a layout child to set its
position within the layout. Any value from 0-9 is accepted.
| flex-order | Sets element order. |
| flex-order-sm | Sets element order on devices less than 600px wide. |
| flex-order-gt-sm | Sets element order on devices greater than 600px wide. |
| flex-order-md | Sets element order on devices between 600px and 960px wide. |
| flex-order-gt-md | Sets element order on devices greater than 960px wide. |
| flex-order-lg | Sets element order on devices between 960px and 1200px wide. |
| flex-order-gt-lg | Sets element order on devices greater than 1200px wide. |


Marks an embedded type as a member for allOf and sets the x-class value. On interface definitions there is another annotation on methods allowed swagger:name
The swagger:allOf annotation can be followed by a string. This string will be the value for the x-class
vendor extension. This value is used as constant for the discriminator field.
An interface that is embedded expects to have 1 method that is commented with Discriminator: true
. That field will be used as discriminator field when marshalling/unmarshalling objects.
Because this is for use with interfaces we can’t make use of the json struct tag to allow for spec name overriding. So instead you can annotate method names on an interface with swagger:name and a value this will then provide the json field name.
swagger:allOf org.example.something.TypeName
// TeslaCar is a tesla car
//
// swagger:model
type TeslaCar interface {
// The model of tesla car
//
// discriminator: true
// swagger:name model
Model() string
// AutoPilot returns true when it supports autopilot
// swagger:name autoPilot
AutoPilot() bool
}
// The ModelS version of the tesla car
//
// swagger:model modelS
type ModelS struct {
// swagger:allOf com.tesla.models.ModelS
TeslaCar
// The edition of this Model S
Edition string `json:"edition"`
}
// The ModelX version of the tesla car
//
// swagger:model modelX
type ModelX struct {
// swagger:allOf com.tesla.models.ModelX
TeslaCar
// The number of doors on this Model X
Doors int32 `json:"doors"`
}
---
definitions:
TeslaCar:
title: TeslaCar is a tesla car
type: object
discriminator: "model"
properties:
model:
description: The model of tesla car
type: string
x-go-name: Model
autoPilot:
description: AutoPilot returns true when it supports autopilot
type: integer
format: int32
x-go-name: AutoPilot
modelS:
allOf:
- $ref: "#/definitions/TeslaCar"
- title: The ModelS version of the tesla car
properties:
edition:
description: "The edition of this model S"
type: string
x-go-name: Edition
x-class: "com.tesla.models.ModelS"
x-go-name: "ModelX"
modelX:
allOf:
- $ref: "#/definitions/TeslaCar"
- title: The ModelX version of the tesla car
properties:
doors:
description: "The number of doors on this Model X"
type: integer
format: int32
x-go-name: Doors
x-class: "com.tesla.models.ModelX"
x-go-name: ModelX
12 Dec 2015 #polymorphism


Context
3D Animation made in Maya
Role
Model, Animation, Texture, Lighting
Team
Kenny Cheung, Tamiko Tadeo, Wade Liu, Gordon Huang
Kactus Und Panzer is an animation modeled and animated in Autodesk Maya. The story take places in a wasted desert located in North Africa. It documented the intense battle between the German Sherman tank and the enemy Tiger Tank. The Tiger tanks has the advantage of being heavily armed with thick armor and deadly weapon. Whereas the Sherman tank is designed as a quick and swift tank with relatively better movement speed with the trade off of lacking armor and firepower. The battle starts with Sherman manuver around the Tiger to dodge its power shots while shooting back. The close battle lead up to the climax when the track of the Tiger is damaged, which stopped it from moving. Simultaneously, the Sherman is coming closer and closer with gradually increasing in fire precision. The critical shot ended the battle was the well placed shot from the Tiger, brutally blown the Sherman tank into pieces.
In this project, I contributed in the modeling, texturing and animation process. I am responsible to create the detailed models of the tank and texture the with material and bump maps. Also, I had to animate them according to the script we established.
I am filled with passion when I model the tanks. Each detail pieces require different workflows in maya in order to achieve the required shape. For example, the tank track is a complicated shape combined with multiple steel plates. Not only do we have to model a highly detailed steel plate, we also need to align the plates into the shape of a ellipse. One of the problem was to rig it so that when it is rotated, the track pieces follow a path to maintain the overall shape of the ellipse. The method we used was using the “wire” tool. Its principle was to bind the circular aligned track to a circular wire. After that is done, we will be able to control its vertex points and manipulate its shape. With that setup, the rotation will always follow the same shape manipulated by the wire.
One of the most time consuming processes was associated with animation. We understood the importance of working out details through the iterate process. To animate objects and provide liveliness, we trained ourselves to use the graph animation editor in order to achieve natural movement recoil. They are small detail that are not negligible. If we look at how objects moves in real life with momentum, when an object changes its movement direction or stops, there are most likely recoil that makes it goes back and forth when stopping. With graph editor, we were able to refine our animation curves into smooth lines that revolves around the origin back and forth. As a result, we achieved more lively animation that can communicate an object's weight and momentum.
I really enjoyed working on this project. Despite it being stressful and challenging, I feel that I have learned more than just the modeling and animation workflow, but more of the mentality of iterating through a model, texture and its motion as close to reality as possible. Through continue refinement without compromisation, I believe I am able to create an alternate reality within viewer's screen that is convincing.


-
Vibe
Alexithymia is a subclinical condition characterized by impaired awareness of one's emotional states, which has profound effects on mental health and social interaction.
Before starting the test, please make sure that your webcam is working.
Start Test


@Retention(value=RUNTIME)
public @interface AllowAnonymousAccess
| Modifier and Type | Optional Element and Description |
|---|---|
boolean |
attemptOptionalAuthentication
The attemptOptionalAuthentication attribute is a hint to the servlet
whether authentication headers should be processed when handling services
with the AllowAnonymousAccess annotation.
|
boolean |
fetchContributor
The fetch contributor attribute lets the servlet know if the contributor record needs to
be fetched.
|
public abstract boolean attemptOptionalAuthentication
If the value is false and the incoming request includes OAuth headers, then the headers will not be processed. If the value is true and the incoming request includes OAuth headers, then the servlet will try to process the OAuth headers to discern an authenticated user.
public abstract boolean fetchContributor


What's up! My name is Tahiana Araujo, a.k.a. Taia Rock, I´m a Brazilian UX Designer and Information Architecture based in Rio de Janeiro. I create beautiful functional web projects and other stuff.
Mobile + User Interface + Information Architecture
App developed to "Metrô Rio" (Subway of Rio de Janeiro). Everything was done in a very short time. I applied concepts and process based on UX and Information architecture when I was doing the interface design and that was the key to do a clean and functional app.
Marido Pão duro
User Interface + Information Architecture + Concept Content + Logo Design
Content and Interface design for the collective purchasing website “Marido Pão Duro”, initially conceptualized by entrepreneur Jonathan Habib. Biggest challenge was to gather attention between its similar competition, given a playful tone based on points and rewards.
Facetouch
User Interface + Information Architecture + Content
Interface design to be installed in touchscreen device placed in nightclubs/bars. Main objective is to be a picture-sharing tool, with a mandatory white background to illuminate the users.
Blog do Lula
User Interface + Information Architecture + ID
Prototype of a Interface design for the former Brazil President Lula da Silva’s blog, in development while working for MPI Digital. The blog’s objective was to be a direct tools with its former voters, thus a simple and clean interface was chosen.
MPI Digital
User Interface + Concept Content + Infographic
Interface design and Content conceptualization of the new website for the MPI Digital, an agency centered in Political marketing, but with the objective of reaching out for more clients outside its original focus.


What is CAAT ?
It is a
CAAT stands for Canvas Advanced Animation Tookit.
This name, is somehow obsolete. First of all, the rendering engine is not only focused on Canvas. WebGL and CSS can be selected too. There's also a native implementation which executes CAAT seamlessly on iOS and Android.
CAAT it is a complete gaming framework, featuring on-screen entities, custom matrix stack, game loop hooks, scenes, scene transition, affine transformations, pixel perfect on-screen entity identification, complex paths, behaviors, seamless box2d integration, etc.
This tutorial is divided in 10 chapters which describe the following CAAT features:


Press n or j to go to the next uncovered block, b, p or k for the previous block.
| File | Statements | Branches | Functions | Lines | |||||
|---|---|---|---|---|---|---|---|---|---|
| board.js |
|
81.25% | 13/16 | 50% | 4/8 | 100% | 2/2 | 81.25% | 13/16 |
| chess-controller.js |
|
91.84% | 45/49 | 66.67% | 4/6 | 100% | 5/5 | 91.11% | 41/45 |
| chess-model.js |
|
77.78% | 7/9 | 50% | 2/4 | 100% | 1/1 | 77.78% | 7/9 |
| chess-view.js |
|
77.78% | 7/9 | 50% | 2/4 | 100% | 1/1 | 77.78% | 7/9 |
| classic-eight-queens.js |
|
78.85% | 41/52 | 87.5% | 21/24 | 88.89% | 8/9 | 80.43% | 37/46 |
| general-eight-queens.js |
|
85.71% | 66/77 | 90.32% | 28/31 | 92.31% | 12/13 | 86.96% | 60/69 |
| matrix.js |
|
100% | 9/9 | 50% | 1/2 | 100% | 5/5 | 100% | 9/9 |
| output.js |
|
75% | 3/4 | 50% | 1/2 | 100% | 1/1 | 75% | 3/4 |
| painter.js |
|
88.89% | 8/9 | 75% | 3/4 | 50% | 1/2 | 88.89% | 8/9 |
| strategy-manager.js |
|
83.33% | 5/6 | 50% | 1/2 | 75% | 3/4 | 83.33% | 5/6 |


 Our team has innnovated a platform that both trainers and clients can utilize to keep attendance and scheduling for fitness classes in one, centralized location.
Let's Progress Together
We at Anywhere Fitness want to make progress just the same as you do! This application will grow and "gain" just the same as you will in your fitness adventures! Expect many new features and benefits to come!
Sign Up for a Free Trial!
We here at Anywhere Fitness wants you to explore the benefits offered through our appllication so much that we are offering a free month trial! click here to sign up as a trainer or as a client
Contact Us
Anywhere Fitness
9095 E. Tanglewood St.
Lakeland, FL 33801
Email:
<EMAIL_ADDRESS>Phone
(555)123-4567


The Line-Up: Edge of the Bay, Struggling Kings and a grand opening
by Kyron SmithsonWow Balmy Nights was absolutely amazing, thanks to everyone involved in making it such a golden evening.
And a thank you to everyone who came along, such a brilliant vibe, much love to you all, and on we roll.
The Shire of Esperance is set to deliver its fourth Edge Of The Bay Festival on Saturday, November 30.
The festival is based around the Youth Precinct on the Esperance Foreshore.
From 2pm, the skate park will come alight with The Battle of The Bay showcasing a high energy skate, scoot and BMX competition featuring local and out of town riders.
Market stalls, pop up eateries, beers by Lucky Bay Brewery and a myriad of community events will turn the area into a vibrant hub for the afternoon.
At 6pm we will see the commencement of the live music element of the day, kicking off with cruisy rock and roll performed by 2019 WAM best Indigenous act The Struggling Kings.
They will be followed at 7pm by multi-instrumentalist James Wilson.
The night hots up with two Esperance favourites, Michael Dunstan at 8pm and Grand Casual closing the evening out from 9pm.
Promises to be an epic day make sure to get down early to enjoy the full day's festivities.
Livy has been a mainstay at the events I have been putting together at The Cannery, delivering tasty Gozlemes, Tacos, and for Balmy Nights a stunning smoked food platter.
Absolutely wrapped to see her stepping out to launch her pop-up café.
The Grand Opening is set for Sunday, November 24 from 7am-1.00pm on The Esplanade (Mini Golf).
Livy's food is amazing and I can't wait to see what she is putting together for us.
Livy's will be family and dog friendly.
People are invited to BYO picnic blanket and chairs.
Vegan and gluten free options will be offered, and there will be lots of activities for the kids.
And to round it out, Grand Opening wiIl be having a bit of a busk from around 9.30pm.
Get on down and support a fantastic lady as she delivers a tasty Sunday Brunch.


September 13, 2021
What is Emotional Intelligence?
Emotional Intelligence is being able to effectively manage and control the effect your emotions have on your feelings and how they’re expressed in everyday life. Through improving our own Emotional Intelligence we can more accurately perceive and identify our own emotions and even better recognise those emotions in others. This in turn helps us interact with others in work, life, and love across the board. Through listening better and interpreting the words more clearly it helps you to have far more empathetically charged conversations.
How is it different to IQ?
IQ is our more rational, analytical, and logic-based area of the brain and it is expressed through how well we problem-solve and reason with an issue. IQ by its nature differs from EQ in that it can be measured in tests, stats, figures, and scores. They also differ in the ways a person collects information: someone with a lot of EQ will focus on the intent behind what is being said or written down and the ways in which that information might improve their wellbeing or help others; whereas someone who’s more IQ driven will collect and retain that information far more effectively and will be better suited for recalling or using that knowledge later. This can have drawbacks of course because sometimes forming an opinion on that information or how it might benefit others isn’t even considered.
In computing circles, A.I (Artificial Intelligence) exists already everywhere because information collection and retrieval is easy for a machine to replicate; but A.E.I (Artificial Emotional Intelligence) on the other hand is considered a new frontier in research, and a long, long way off from even being properly understood let alone implemented. The neural pathways required for emotional thought concepts are just so much more complex.
Why is EQ important?
It just has so many benefits, it can decrease your stress levels in life or work, help build better relationships where needed. Help a team work better, help individuals work more productively alone and converse better with others. Being more emotionally engaged helps you become a more rounded, and overall better human being. It is an innate human quality and ability and we should all embrace it as thinking and flourishing human beings.


On theory development in design science research: anatomy of a research project
Authors
Bill Kuechler and Vijay Vaishnavi
Status
Unread
Relevance
Quotations
Notes
References
Concepts
Field of Study
Methodology


--- layout: page title: About header-img: "img/about-bg.png" ---
I am an accountant and have 6+ years of experience.


Popular Areas in clean lint from dryer
Clean Out Your Dryer Lint (17/365) - The Simple Dollar
Jan 18, 2012 . This seems like such a simple thing. Most of us do this as a matter of course whenever we dry a load of laundry in our dryer. Forgetting to do it, .
http://www.thesimpledollar.com/2012/01/18/clean-out-your-dryer-lint-17365/
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Remove the Lint Trap Filter From Dryer and Brush it Clean to Remove Lint. © 2009 Home-Cost.com. Remove the Lint Trap Filter This is the step you are most .
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Mary asked: How do I clean a dryer lint screen that is already coated with a residue? I bought a used dryer that looked great, but the dryer lint screen is.
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Dryer - Maintenance Tips for your Dryer
If the lint build-up is severe, it's important to disassemble the dryer and clean out the lint more thoroughly. This is often a job .
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Dryer Lint Cleaning Tips | The Family Handyman
Dryer Lint Cleaning Tips, Prevent house fires. Clean the lint from inside your clothes dryer as well as lint caught in the exhaust vent. You can complete the .
http://www.familyhandyman.com/DIY-Projects/Home-Repair/Appliance-Repair/dryer-lint-cleaning-tips/View-All


Karen S. Tompkins
MADISON - Karen S. Tompkins, age 70, of Madison, passed away on Sunday, Nov. 17, 2019, at Agrace HospiceCare.
She was born on Nov. 21, 1948, in Madison, the daughter of Earl Wood and Dorothy (Adler) Coenen.
Karen was employed for 43 years with WPS Insurance. She enjoyed trips to the casino, reading, and enjoying her coffee on her porch while soaking up the sun.
Karen is survived by her daughter, Nicole (Gregory) Plunkett; grandsons, Devin and Aaron (Amanda Yang) Hoffmaster; granddaughter, Raven Oren; step-granddaughter, MacKenzie Plunkett; step-grandson, Blake Plunkett; brother, Michael Coenen; sister, Kathy (Ken) Forslin; three step-sisters, Denise Baerwolf, Debby Leake and Diane Schulz; half-sister, Deb Nelson; and many nieces, nephews, and other relatives, and friends. Karen was preceded in death by her parents; and brothers, Craig, Walter, and Gary Wood.
Per Karen's wishes, services were private.
Memorials may be gifted in Karen's name to Agrace HospiceCare
Online condolences may be made at www.gundersonfh.com.
Gunderson East
Funeral & Cremation Care
5203 Monona Drive
(608) 221-5420


Press and hold a note or chord using computer keyboard or choose a MIDI controller from below.
A neural network will arpeggiate around your chord.
Using the Improv RNN (pretrained) model from Google Magenta, and Magenta.js + TensorFlow.js + Tone.js.


homura.modules package¶
Subpackages¶
Submodules¶
homura.modules.attention module¶
homura.modules.conditional_batchnorm module¶
-
class
homura.modules.conditional_batchnorm.
CategoricalConditionalBatchNorm
(num_features, num_classes, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)[source]¶ Bases:
torch.nn.modules.batchnorm._BatchNorm
(Categorical) conditional batch normalization, proposed in V. Dumoulin, J. Shlens, and M. Kudlur, “A learned representation for artistic style”, https://arxiv.org/abs/1610.07629 (In this paper, conditional instance normalization is used)
- Parameters
num_features –
num_classes –
eps –
momentum –
affine –
track_running_stats –
-
forward
(inputs: torch.Tensor, categories: torch.Tensor) → torch.Tensor[source]¶ Defines the computation performed at every call.
Should be overridden by all subclasses.
Note
Although the recipe for forward pass needs to be defined within this function, one should call the
Module
instance afterwards instead of this since the former takes care of running the registered hooks while the latter silently ignores them.
homura.modules.discretization module¶
-
class
homura.modules.discretization.
GumbelSigmoid
(temp: float = 0.1, threshold: float = 0.5)[source]¶ Bases:
torch.nn.modules.module.Module
This module outputs gumbel_sigmoid while training and input.sigmoid() >= threshold while evaluation
-
forward
(input: torch.Tensor) → torch.Tensor[source]¶ Defines the computation performed at every call.
Should be overridden by all subclasses.
Note
Although the recipe for forward pass needs to be defined within this function, one should call the
Module
instance afterwards instead of this since the former takes care of running the registered hooks while the latter silently ignores them.
-
-
class
homura.modules.discretization.
GumbelSoftmax
(dim: int, temp: float = 0.1)[source]¶ Bases:
torch.nn.modules.module.Module
This module outputs gumbel_softmax while training and argmax in onehot fashion while evaluation
-
forward
(input: torch.Tensor) → torch.Tensor[source]¶ Defines the computation performed at every call.
Should be overridden by all subclasses.
Note
Although the recipe for forward pass needs to be defined within this function, one should call the
Module
instance afterwards instead of this since the former takes care of running the registered hooks while the latter silently ignores them.
-
-
class
homura.modules.discretization.
StraightThroughEstimator
[source]¶ Bases:
torch.nn.modules.module.Module
-
forward
(input: torch.Tensor)[source]¶ Defines the computation performed at every call.
Should be overridden by all subclasses.
Note
Although the recipe for forward pass needs to be defined within this function, one should call the
Module
instance afterwards instead of this since the former takes care of running the registered hooks while the latter silently ignores them.
-
-
class
homura.modules.discretization.
SemanticHashing
[source]¶ Bases:
torch.nn.modules.module.Module
-
forward
(input: torch.Tensor) → torch.Tensor[source]¶ Defines the computation performed at every call.
Should be overridden by all subclasses.
Note
Although the recipe for forward pass needs to be defined within this function, one should call the
Module
instance afterwards instead of this since the former takes care of running the registered hooks while the latter silently ignores them.
-
homura.modules.miscs module¶
homura.modules.regularizer module¶
-
class
homura.modules.regularizer.
WSConv2d
(in_channels, out_channels, kernel_size, stride=1, padding=0, dilation=1, groups=1, bias=True, padding_mode='zeros')[source]¶ Bases:
torch.nn.modules.conv.Conv2d
nn.Conv2d with weight standardization
-
forward
(input: torch.Tensor) → torch.Tensor[source]¶ Defines the computation performed at every call.
Should be overridden by all subclasses.
Note
Although the recipe for forward pass needs to be defined within this function, one should call the
Module
instance afterwards instead of this since the former takes care of running the registered hooks while the latter silently ignores them.
-
homura.modules.vq module¶
-
class
homura.modules.vq.
VQModule
(emb_dim: int, dict_size: int, update_dict_by_ema: bool = False, gamma: float = 0.99, epsilon: float = 1e-05)[source]¶ Bases:
torch.nn.modules.module.Module
-
forward
(input: torch.Tensor) → Tuple[torch.Tensor, torch.Tensor][source]¶ Defines the computation performed at every call.
Should be overridden by all subclasses.
Note
Although the recipe for forward pass needs to be defined within this function, one should call the
Module
instance afterwards instead of this since the former takes care of running the registered hooks while the latter silently ignores them.
-


Contract
| Vendor Name | LABO S M INC, GROUP ABS INC., EN CONSORTIUM |
|---|---|
| Description of Work | Engineering construction consultant |
| Comments | Owner’s Laboratory services for the execution of sampling, testing and various laboratory services, as well as providing support in quality assurance and quality control pertaining to the New Champlain Bridge Corridor Project. This contract was awarded as a result of a Public Works and Government Services Canada competitive process. |
| Reference Number |<PHONE_NUMBER> |
| Contract Date | 2015-07-24 |
| Contract Period | 2015-07-24 to 2021-12-31 |
| Contract Value | $ 2,165,841.56 |
* Use either Contract Period or Delivery Date.


Oro Valley, AZ
Catalina State Park
The Hike
This was a great hike. The trail was wide the entire time with not much elevation gain, so it was doable in the heat of the summer. Dara (our dog) loved every moment of it and the sweeping views around every corner made this a low effort, high reward hike for all involved. There is a $7 entrance fee to Catalina State Park.
The Details
| Trail Name |
Park Name
|
Length of Trail (miles)
|
Hike Time (HH:MM)
|
Elevation Gain (feet)
|
Loop? |
Canyon Loop Trail
|
Catalina State Park
|
2.3
|
01:15 |
200
|
Yes |
Dog friendly?
|
Shade? |
Amount of water brought
|
Distance from Home (miles)
|
Time of Year
|
Time of Day
|
Yes - wide open sandy trail
|
Not too bad, there was some
|
3 large Aquafina bottles (used 1), 2 Camelback (used 2)
|
11.6
|
Summer (06/29)
|
Started at 7:30 AM |


The GitHub credentials
Supports username/password, username/accessToken, or accessToken
If you're using a Personal Access Token the token should have at least repo_status access


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{% extends 'base.html' %} {% comment %} # Copyright 2017 Lockheed Martin Corporation # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # {% endcomment %} {% load bootstrap3 %} {% block title %} Edit Mission Hosts {% endblock %} {% block main_heading %}
| Name | IP Address | No-Hit | Actions |
|---|---|---|---|
| {{ host.host_name }} | {{ host.ip_address }} | {% if host.is_no_hit %} Yes {% else %} No {% endif %} | {% bootstrap_icon "pencil" %} {% bootstrap_icon "trash" %} |


U.S. government sees no evidence of hacking in Tuesday's elections
(Reuters) - Voting in U.S. state and local elections on Tuesday showed no evidence of successful tampering by any foreign government, the Justice Department and six U.S. security agencies said.
But Russia, China, Iran and other adversaries of the United States will seek to meddle in U.S. elections moving forward, including through social media manipulation and cyberattacks, the agencies said.
“While at this time we have no evidence of a compromise or disruption to election infrastructure that would enable adversaries to prevent voting, change vote counts or disrupt the ability to tally votes, we continue to vigilantly monitor any threats to U.S. elections,” a joint statement, signed by the heads of each agency, said.
The agencies have increased efforts to protect elections and a new position was created within the Office of the Director of National Intelligence to focus solely on U.S. election security
A January 2017 assessment by U.S. intelligence agencies found that Russia had meddled in the 2016 presidential election and its goals included aiding President Donald Trump.
National security experts have said they believe foreign governments will again target the 2020 presidential election in an effort to influence U.S. voters.
In February 2018, the Justice Department created the first ever Cyber Digital Task Force with the mission of protecting future U.S. elections from foreign interference.


contact
home
home
Sales Table in each Store
Salmon Cookies
salmon cookies
store Name
minimum order
maximum order
avgCookie


public class CertificateValidator
extends java.lang.Object
implements org.bouncycastle.crypto.tls.TlsAuthentication
HttpsConnectionImpl.isAllowUntrustedCertificates()
is true then
this certificate validator will ignore almost all mismatching attributes
(validity, common name, signer , etc.). The only "always fatal" error is an
invalid certificate signature when validated against the issuer public key,
meaning that the server certificate was modified in transit. However, it is
important to mention that if
HttpsConnectionImpl.isAllowUntrustedCertificates()
is true and no
issuer certificate was provided, than the validation will still return "ok".
The above mentioned "fatal exception" will occur only if the issuer/signer
certificate is provided and the server certificate's signature can not
validated using it.| Constructor and Description |
|---|
CertificateValidator(HttpsConnectionImpl httpsConnectionImplInstance)
Creates a new validator instance.
|
| Modifier and Type | Method and Description |
|---|---|
org.bouncycastle.crypto.tls.TlsCredentials |
getClientCredentials(org.bouncycastle.crypto.tls.CertificateRequest certificateRequest)
TlsAuthentication.getClientCredentials(CertificateRequest)
CLIENT AUTHENTICATION NOT SUPPORTED. |
HttpsConnectionImpl |
getHttpsConnectionImplInstance()
|
void |
notifyServerCertificate(org.bouncycastle.crypto.tls.Certificate serverCertificate)
See
TlsAuthentication.notifyServerCertificate(Certificate) |
void |
setHttpsConnectionImplInstance(HttpsConnectionImpl httpsConnectionImplInstance)
|
protected boolean |
validateCertificate(org.bouncycastle.asn1.x509.Certificate cert,
org.bouncycastle.asn1.x509.Certificate issuerCert,
java.util.List errors)
Validates whether the certificate is valid and if it was signed by the
corresponding issuer Certificate/Key.
|
protected void |
validateServerCertificatePurposeAndCommonName(java.util.Hashtable serverCertInfo,
java.util.List errors)
Validates the server common name and the certificate extended key usage attribute.
|
protected boolean |
verifyEndDate(org.bouncycastle.asn1.x509.Certificate cert,
java.util.List errors)
Validates if the certificate's "end date" is valid.
|
protected boolean |
verifyServerCertificateCommonName(java.util.Hashtable serverCertificateInfo,
java.util.List errors)
Validates if the certificate's common name matches the server's hostname
used in the HTTPS connection.
|
protected boolean |
verifySignature(org.bouncycastle.asn1.x509.Certificate cert,
org.bouncycastle.asn1.x509.Certificate issuerCert,
java.util.List errors)
Validates the certificate signature (hash).
|
protected boolean |
verifyStartDate(org.bouncycastle.asn1.x509.Certificate cert,
java.util.List errors)
Validates if the certificate's "start date" is valid.
|
public CertificateValidator(HttpsConnectionImpl httpsConnectionImplInstance)
httpsConnectionImplInstance
- the HttpsConnectionImpl instance owning the certificate to be validated. See
HttpsConnectionImpl
.public HttpsConnectionImpl getHttpsConnectionImplInstance()
HttpsConnectionImpl
public void setHttpsConnectionImplInstance(HttpsConnectionImpl httpsConnectionImplInstance)
httpsConnectionImplInstance
- HttpsConnectionImpl
protected boolean validateCertificate(org.bouncycastle.asn1.x509.Certificate cert, org.bouncycastle.asn1.x509.Certificate issuerCert, java.util.List errors) throws org.bouncycastle.operator.OperatorCreationException, org.bouncycastle.cert.CertException, CertificateValidationException
cert
- the certificate to be validated.issuerCert
- the issuer (normally a C.A.) certificate corresponding to the
key used to sign the certificate indicated at the previous
parameter.errors
- a list to be filled - if needed - with errors detected during
the validation process. See
CertificateValidationException.setErrors(List)
.org.bouncycastle.cert.CertException
org.bouncycastle.operator.OperatorCreationException
CertificateValidationException
protected boolean verifySignature(org.bouncycastle.asn1.x509.Certificate cert, org.bouncycastle.asn1.x509.Certificate issuerCert, java.util.List errors) throws org.bouncycastle.operator.OperatorCreationException, org.bouncycastle.cert.CertException
cert
- The certificate to be validated.issuerCert
- the issuer (normally a C.A.) certificate corresponding to the
key used to sign the certificate indicated at the previous
parameter.errors
- a list to be filled - if needed - with errors detected during
the validation process. See
CertificateValidationException.setErrors(List)
.java.io.IOException
org.bouncycastle.crypto.InvalidCipherTextException
org.bouncycastle.cert.CertException
org.bouncycastle.operator.OperatorCreationException
protected boolean verifyStartDate(org.bouncycastle.asn1.x509.Certificate cert, java.util.List errors)
cert
- The certificate to be validated.errors
- a list to be filled - if needed - with errors detected during
the validation process. See
CertificateValidationException.setErrors(List)
.protected boolean verifyEndDate(org.bouncycastle.asn1.x509.Certificate cert, java.util.List errors)
cert
- The certificate to be validated.errors
- a list to be filled - if needed - with errors detected during
the validation process. See
CertificateValidationException.setErrors(List)
.protected boolean verifyServerCertificateCommonName(java.util.Hashtable serverCertificateInfo, java.util.List errors)
serverCertificateInfo
- The certificate to be validated.errors
- a list to be filled - if needed - with errors detected during
the validation process. See
CertificateValidationException.setErrors(List)
.public void notifyServerCertificate(org.bouncycastle.crypto.tls.Certificate serverCertificate) throws java.io.IOException
TlsAuthentication.notifyServerCertificate(Certificate)
notifyServerCertificate
in interface org.bouncycastle.crypto.tls.TlsAuthentication
java.io.IOException
protected void validateServerCertificatePurposeAndCommonName(java.util.Hashtable serverCertInfo, java.util.List errors) throws CertificateValidationException
verifyServerCertificateCommonName(Hashtable, List)
.CertificateValidationException
public org.bouncycastle.crypto.tls.TlsCredentials getClientCredentials(org.bouncycastle.crypto.tls.CertificateRequest certificateRequest) throws java.io.IOException
TlsAuthentication.getClientCredentials(CertificateRequest)
getClientCredentials
in interface org.bouncycastle.crypto.tls.TlsAuthentication
java.io.IOException


We’ve mastered the technique of reupholstering every aspect of this timeless chair. Our depth of knowledge of the history and breadth of experience with these chairs makes our work second to none. From the leather & the fiberboard to the cushion insert your chair will be restored exactly to spec as the original.
Depending on your preference you have the option to do a full refinish or a light restoration that shows original patina. We will always use the period correct finish for your chair. Chairs from 1956-1979 will get a gunstock oil finish and chairs from 1980 on will receive a spray lacquer finish.
Shock mounts are the rubber absorbers that hold the back of the chair to the seat. Over time, the shock mounts are susceptible to failure and will need repair. We use custom jigs depending on the year of your chair so the positioning is perfect and manufacture our own shock mounts here in the USA made exactly to spec as the originals. Unlike most repair shops we will never drill holes through your eames chair. We utilize the proper black two-part adhesive made specifically for bonding rubber to wood. Our shock mount repair certifies the longevity and value of your Eames


Who Am I?
- 2007 CTO cember.net
got acquired by Xing, yay!
- 2008 Project Director livego.com
gone to deadpool, R.I.P. :(
- 2011 VP of Technology grou.ps
still alive ;)
- 2012 Mobile Engineer Jive Software
that's what I do right now.
- J4V45cR1p7 h4x0R o2js.com
that's my blog!
Outline
- Overview: Front-End Development Best Practices
- Useful JavaScript Patterns & Practices
- A ReIntroduction to JavaScript Memory Leaks
- Profiling JavaScript Applications
- Practice Time: Step by Step Optimizing a Sample Application
- Q&A
Best Practices
(Micro)
- eval is evil
- Avoid try/catch
- Avoid with
- Avoid $.each and for/in loops
- Use String Builders
- Primitive operations are faster than function calls
Best Practices
(Speed & Memory)
- Minimize DOM Size and Depth
- Minimize DOM Repaints and Reflows (cache DOM calculations)
- Keep Your Markup Clean (avoid inline & embedded code)
- Purge Anything that is not Visible (from DOM AND from Memory)
- Async Load Third-Party Widgets
- Smoothness/Speed Tradeoff
Best Practices
(Perceived Speed)
- Load Lazily; Execute Lazily
- Do Not Wait for Server Feedback
- Styles to the Top, Scripts to the Bottom
Best Practices
(Transfer Speed)
- Far Future Expires Header
- Minify Your Assets
- Combine Multiple Assets
- CSS Sprites, Image Data URIs, Image Optimization
- Cache (client-side and server-side) & Gzip
Best Practices (Macro)
- Make JavaScript and CSS External
- Make AJAX Cacheable
- Use a Strict REST Architecture
- Reduce Cookie Size
- Use Cookie-Free Domains for Components
- Make favicon.ico Small and Cacheable
Common Patterns & Practices
Patterns & Practices (Building Blocks)
- Prototypal Inheritance
- Model-View-Whatever (MVC, MVP, MVVM…)
- Module ♥ / AMD
- Continuation Passing Style
- Mixin / Decorator / Dependency Injection
- Façade / PubSub ♥ / Mediator
- Flow Control / Deferreds / Promises ♥
Patterns & Practices (More)
- Chaining
- Factory
- Composite
- Strategy
- Command / Chain of Responsibility
- Bridge
- Flyweight
- Iterator
- Null Object
- Singleton
- and the list goes on…
Using Patterns… Because You Can
Using Patterns…
Without Knowing the Liabilities
Think Simple
- E = MC2
- Simplicity is the Ultimate Sophistication
- When in doubt, KISS.
Memory Leaks (OverView)
- How JavaScript Garbage Collector Works
- Memory Leaks in Older Browsers (read: Internet Explorer)
- Memory Leaks Related to Timers
- Memory Leaks Related to Debug Console
- Size Does Matter
- Structural Leaks
Garbage Collection *
Older Browsers – Event Handler Leak (IE < 8)
Older Browsers – XHR Leak (IE < 9) *
Structural Leaks *
- These Are NOT Because of the Browser Bugs
- They Are the Most Common Leaks
- Handlers, Registries, Controllers, Managers, Mediators, Observables Are Leaker Candidates
- Leaks are in the Nature of Event-Based Architectures
- Closures and Modules Are Controlled Memory Leaks
Good kids clean their mess!
Structural Leaks (jQuery)*
//(1)
elem[jQuery.expando] = ++jQuery.uuid;
//(2)
jQuery.cache[elem[jQuery.expando]]['property'] = 'value';
✓ DOM never references jQuery objects directly.
∴ Removing jQuery elements using native methods can leak.
Beware of the Console Leaks *
Garbage-Collector-Friendly Code *
- Use Variables With a Proper Scope
- Unbind Events
- Clear Timers
- Invalidate Cache
Profiling JavaScript Applications
Profiling JavaScript Applications
Agenda
- Creating a Logical Folder Structure
- Configuring the Builder, Linter, and Tests
(grunt, jshint, jasmine, istanbul)
- Profiling the Application & Fixing Leaks
- Localizing the Application
- Decoupling Modules Using Custom Events (PubSubHub)
- Adding a Mediator (PubSub and Hub)
- Implementing DOM Event Delegation
- Improving Render Performance
- Code Coverage Analysis
- You Need Testing
Folder Structure *
⇨
Configuring Grunt *
Configuring JS Hint
Configuring Jasmine
Configuring Istanbul
Profiling
Fixing Memory Leaks
PubSubHub
Adding a Mediator
PubSub
+
Hub
DOM Event Delegation
Improving Render Performance
Code Coverage Analysis
Unit Testing
Test State (NOT User Interface, NOT Interactions)
Assemble
Act
Assert
Deployment
Thank You
¯\_(ツ)_/¯
Questions?


Lecture 12
Category Theory
Proposed title: Do You Even Lift?
...allows one to see the forest rather than the individual trees, and offers the possibility for study of the structure of the entire forest, in preparation for the next stage of abstraction - comparing forests.
Roots in algebraic topology in the early 1940s by Eilenberg and Mac Lane
It provides a powerful language.
It can translate difficult problems to easy ones.
It features strong abstractions and attempts to unify separate ideas.
A continuous function from a unit circle to itself must have a fixed point.
(Image © Jack E.)
If you crumple up one sheet of paper and place it on top of a flat sheet, then at least one point will be directly over it's corresponding point.
After sloshing around a cup of coffee, at least one point will always remain in the same spot.
Brouwer's Theorem assures existence of solutions to some differential equations.
Brouwer's Theorem assures existence of equilibria in Game Theory.
Let D be the unit-circle disk.
Let S be the surface of the unit-circle.
Lemma: There is no continuous function
h: D → S that leaves each point on S fixed.
Using a Functor, we can transform one Category to another by preserving identities and compositions.
|
|
|
|
|
|
|
By instead examining the Category of Groups, we can conclude that no such group homomorphism g: 0 → Z can exist.
We have proved the Lemma.
GIVEN: Lemma: There is no continuous function
F: D → S that leaves each point on S fixed.
SHOW: A continuous function f: D → D must have a fixed point
...and now, THE DROP!
By way of contradiction, assume ∀x∈D: x ≠ f(x)
Then we can always form the function F: D → S that leaves each point on S fixed.
Contradiction. GG.
A Category C is a collection of Ob(C) and Ar(C).
Ob(C) are the objects of C. Ar(C) are the "arrows" or morphisms of C.Each f:A→B ∈ Ar(C) has it's A and B chosen from Ob(C).
If f:A→B and g:B→C, then there always exists h = g∘f: A→C For every A ∈ Ob(C), there is an identity function idA: A→A.Left and right identity: f∘idA = idA∘f
Associativity: h∘(g∘f) = (h∘g)∘f
Ob(Hask) = the Haskell types. (Bool, [Char], ...)
Ar(Hask) = the Haskell functions. (head, not, ...)
The identity function is id :: a -> a
The axioms are satisfied
Left and right identity: f∘id = id∘f
Associativity: h∘(g∘f) = (h∘g)∘f
Functor F: C→D is a transformation from Category C to Category D
It maps objects in C to objects in D, and functions in C to functions in DFunctor Axioms:
In Haskell, a Functor is a typeclass for things that can be mapped over.
Prelude> fmap odd (Just 3) -- Maybe is a Functor
Just True
Prelude> fmap odd [1..5] -- a list is a Functor
[True,False,True,False,True]
Maybe
Functor1. The type constructor transforms anything of type a
to Maybe a
Like transforming an object in C to an object in D.
Maybe
derives the Functor
typeclass as follows:
instance Functor Maybe where
fmap f (Just x) = Just (f x)
fmap _ Nothing = Nothing
2. fmap transforms a function f: a→b
to Maybe a → Maybe b.Maybe
Functor (Cont.)We just showed that Maybe transforms objects and functions over from the Hask category to the Maybe subcategory.
The Functor Axioms are satisfied:
A Monad is a functor from a Category to itself: M: C→C
And, for every X ∈ Ob(C)
unit: X→M(X)
join: M(M(X))→M(X)
class Functor m => Monad m where
return :: a -> m a
(>>=) :: m a -> (a -> m b) -> m b
Prelude> import Control.Monad
Prelude Control.Monad> :t join
join :: Monad m => m (m a) -> m a
join ∘ M(join) = join ∘ join
Collapsing the inner two layers first, then that with the outer layer is exactly the same as collapsing the outer layers first, then that with the innermost layer.
join ∘ M(unit) = join ∘ unit = id
Applying return to a monadic value, then joining the result should have the same effect whether you perform the return from inside the top layer or from outside it.
Category theory powers Haskell's generalizability.
Homework: Fill out the Course Evaluation


Note: Form must be completed at least 20 minutes prior intended use.
Romance Horror Action Other
I have popcorn!! I have candies!! I have alcohol!! I will provide foodzezzes!! We will be watching a western!! John Wayne is starring!!
In 50 words or more explain what you want to watch.


European car sales zoom to decade-high speed
by AFPEuropean car sales hit their highest October level in a decade, an industry body said Tuesday, as the sector recovers from a stall last year over tighter pollution regulations.
The 8.7 percent rise in registration to 1.18 million vehicles “marked the highest October total on record since 2009,” said the European Automobile Manufacturers Association.
Year-on-year comparisons are inflated as a number of carmakers had difficulty meeting the stricter pollution WLTP measuring methodology that went into force on September 1, 2018, sending sales more than seven percent lower in October last year.
Over the first 10 months of this year, sales are 0.7 percent lower compared to the same period last year.
A global growth slowdown triggered by trade wars and Brexit uncertainty has hit the car industry particularly hard, with German carmaker Volkswagen saying last month that worldwide demand has fallen around five percent.


Virginia Democrats’ Speaker Pick Would Be First Woman in Job
by ASSOCIATED PRESSRICHMOND, Va. (AP) — Virginia’s House of Delegates is expected to soon have its first female speaker in its 400-year history, as the chamber’s incoming Democrats chose a veteran legislator for the post Saturday.
Democratic delegates for the upcoming session picked Del. Eileen Filler-Corn of Fairfax County as their nominee.
Filler-Corn’s election as speaker on the session’s first day in January is anticipated because Democrats on Tuesday won a majority in the state House for the first time in two decades.
Republicans lost their slim seat advantages in both the state House and Senate , giving Democrats led by Gov. Ralph Northam the ability to pass stricter gun laws and a higher minimum wage, as well as change rules barring the removal of Confederate war memorials.
“This is a tremendous honor I don’t take lightly and I’m ready to move forward,” Filler-Corn told the Richmond Times-Dispatch. “We had a historic night on Tuesday and we had a historic day today, so I’m looking forward to continuing to stand up for the issues and values that are so important to Virginians. And we’re thrilled to be in the majority.”
House Democratic Caucus members on Saturday also picked Del. Charniele Herring of Alexandria as the new majority leader, meaning she’ll be the first woman and first African American to hold that job.
Tuesday was the third election in a row that Virginia Democrats have made significant gains since President Donald Trump was elected.
In a news release, Northam said he and the House Democratic leaders that were picked Saturday “share a commitment to serving Virginians and advancing a more progressive and inclusive Commonwealth.”
Filler-Corn, who joined the General Assembly in 2010, would also be the first Jewish speaker in state history. She’d succeed GOP House Speaker Kirk Cox.
Outgoing House Majority Leader Todd Gilbert congratulated Filler-Corn and other new Democratic leaders. He said Republicans are concerned they are all from “the deepest parts of northern Virginia” and want to ensure people in other parts of the state get a fair hearing.
Filler-Corn said she would ensure geographic diversity in committee chairmanships.
Filler-Corn, 55, works for a lobbying and consulting firm in northern Virginia. She doesn’t lobby Virginia state government and will continue to recuse herself from certain state legislative matters that the firm works on, a spokeswoman has said.
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